Livestock Challenge Models of Rift Valley Fever for Agricultural Vaccine Testing
Bibliographic record
Abstract
Since the discovery of Rift Valley Fever virus (RVFV) in Kenya in 1930, the virus has become widespread throughout most of Africa and is characterized by sporadic outbreaks. A mosquito-borne pathogen, RVFV is poised to move beyond the African continent and the Middle East and emerge in Europe and Asia. There is a risk that RVFV could also appear in the Americas, similar to the West Nile virus. In light of this potential threat, multiple studies have been undertaken to establish international surveillance programs and diagnostic tools, develop models of transmission dynamics and risk factors for infection, and to develop a variety of vaccines as countermeasures. Furthermore, considerable efforts to establish reliable challenge models of Rift Valley fever virus have been made and platforms for testing potential vaccines and therapeutics in target species have been established. This review emphasizes the progress and insights from a North American perspective to establish challenge models in target livestock such as cattle, sheep, and goats in comparisons to other researchers' reports. A brief summary of the potential role of wildlife, such as buffalo and white-tailed deer as reservoir species will also be discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".